![]() ![]() When researchers recruit study participants based on proximity or ease of access, their results can’t be representative of the population. Non-probability sampling designs like convenience sampling are almost always biased. There are two main sources of undercoverage bias: Nonresponse means that some units are included in the sample, but their responses are missing. In other words, undercoverage means that some units never make it into the sample or are inadequately represented. Nonresponse bias occurs when some of the respondents you selected to be in your sample don’t respond.Undercoverage bias occurs when some members of a population are totally excluded from the sample frame you use for your study.nonresponse biasĪlthough undercoverage bias and nonresponse bias may seem similar, they are actually quite different. If your sampling frame excludes a large part of your target population, you need to step back and consider how the excluded units may systematically differ from those included in your sample. If however, you are interested in people’s voting intentions, running an online survey excludes a significant part of the population, leading to undercoverage bias. If your research is on online shopping habits, opting for an online survey is a legitimate choice. Previous research shows that internet access also relates to demographics like socioeconomic status and age.ĭepending on your research objective, this may impact your results. The included segments are different from the excluded ones in terms of one or more variables of interestĮxample: Undercoverage biasOnline surveys exclude people who don’t have internet access.Some segments of the population have not been included in your sample but should have been.Keep in mind that two things must both happen for undercoverage bias to occur: In more extreme cases, researchers may completely fail to include a part of the population, which can distort the findings completely. However, if the segment is larger, it can lead to a sample that doesn’t accurately capture the characteristics of the population. If the segment is small in comparison to others in the population, this may not impact the research findings much. In some cases, researchers may sample too few units from a specific segment of the population. In other words, researchers aim to collect a representative sample. Ideally, researchers should draw a sample that, like a snapshot, adequately captures characteristics that are both present in the target population and relevant for the research. Undercoverage bias is the systematic distortion of a study’s findings due to the way the sample was selected. ![]()
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